Name
Title | ||
|---|---|---|
Social trust model for rating prediction in recommender systems: Effects of similarity, centrality, and social ties. |
Abstract | ||
|---|---|---|
The success of e-commerce companies is becoming increasingly dependent on product recommender systems which have become powerful tools that personalize the shopping experience for users based on user interests and interactions. Most modern recommender systems concentrate on finding the relevant items for each user based on their interests only, and ignore the social interactions among users. Some recommender systems, rely on the ‘trust’ of users. However in social science, trust, as a human characteristic, is a complex concept with multiple facets which has not been fully explored in recommender systems. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.osnem.2018.05.001 | Online Social Networks and Media |
Field | DocType | Volume |
Recommender system,PageRank,Pearson product-moment correlation coefficient,Vector space,Social network,Collaborative filtering,Computer science,Centrality,Artificial intelligence,Interpersonal ties,Machine learning | Journal | 7 |
ISSN | Citations | PageRank |
2468-6964 | 4 | 0.38 |
References | Authors | |
26 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anahita Davoudi | 1 | 7 | 1.46 |
| Mainak Chatterjee | 2 | 1562 | 175.84 |